Method and device for determining carbon emission reduction intensity index of new energy kilowatt-hour electricity

Abstract

The invention relates to a method and device for determining a carbon emission reduction intensity index of new energy per kilowatt hour, and the method comprises the steps: building a relation characteristic model between the output of a fossil energy unit and carbon emission based on the output of the fossil energy unit, building a power system carbon emission time sequence simulation pre-evaluation model based on a source, network, load and storage model, a reference installation scene and different new energy installation scenes are defined, and carbon emission and new energy generating capacity of the reference installation scene are calculated based on a relation characteristic model between fossil energy unit output and carbon emission and a power system carbon emission time sequence simulation pre-evaluation model. And obtaining a new energy kilowatt-hour carbon emission reduction intensity index based on difference values between the different new energy installation scenes and the carbon emission and the new energy generating capacity of the reference installation scene and between the different new energy installation scenes and the carbon emission and the new energy generating capacity of the reference installation scene. Through the method and the device provided by the embodiment of the invention, the equivalent carbon emission reduction benefit of new energy grid-connected power generation can be accurately estimated.

Description

Technical Field

[0001] This invention relates to the field of carbon emission pre-assessment technology for power systems, and more specifically, to a method and apparatus for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources. Background Technology

[0002] Building a new power system and replacing fossil fuel power generation with renewable energy sources such as wind and solar power on a large scale is a key path for my country to achieve its "dual carbon" goals and a low-carbon transformation of its energy and power sector. In this process, the Clean Development Mechanism (CDM), as an important international cooperation mechanism for carbon emission reduction, has a valuable reference system for its Certified Emission Reduction (CER) measurement system.

[0003] Under the CDM mechanism, the current main method for measuring carbon dioxide emission reduction is based on the annual grid carbon dioxide baseline emission factor recently released by the National Climate Strategy Center. This measures the carbon emission reduction per kilowatt-hour generated by new energy projects, which is the equivalent carbon emission reduction of new energy replacing fossil fuel power generation. However, as the installed capacity of new energy increases, the system's absorption capacity is gradually reaching saturation. It is necessary to fully tap the system's peak-shaving capacity through measures such as the flexible transformation of thermal power plants or the configuration of energy storage to enhance power system flexibility. For fossil fuel power generating units, coal consumption for power generation will increase significantly with the increase in peak-shaving depth, especially in the deep peak-shaving zone, where the growth rate of coal consumption for power generation will further accelerate. For energy storage, such as pumped hydro storage, the energy conversion rate is between 70% and 75%, meaning that energy loss during the pumping-to-power conversion process is between 25% and 30%, which is equivalent to indirectly consuming additional fuel on the power generation side of fossil fuel units, increasing carbon emissions. Currently, there is no assessment method that considers the above factors for the equivalent carbon emission reduction. Summary of the Invention

[0004] In view of this, the present invention proposes a method and apparatus for determining the carbon emission reduction intensity index of new energy per kilowatt-hour, aiming to solve one or more of the technical problems mentioned in the background section above.

[0005] In a first aspect, embodiments of the present invention provide a method for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources. The method includes: establishing a characteristic model of the relationship between the output of fossil energy units and carbon emissions based on the output of fossil energy units; establishing a time-series simulation pre-evaluation model of carbon emissions in the power system based on a source-grid-load-storage model; identifying a baseline installed capacity scenario, and calculating the carbon emissions and new energy power generation of the baseline installed capacity scenario based on the characteristic model of the relationship between the output of fossil energy units and carbon emissions and the time-series simulation pre-evaluation model of carbon emissions in the power system; constructing different new energy installed capacity scenarios, and calculating the carbon emissions and new energy power generation under different new energy installed capacity scenarios based on the characteristic model of the relationship between the output of fossil energy units and carbon emissions and the time-series simulation pre-evaluation model of carbon emissions in the power system; and obtaining the carbon emission reduction intensity index per kilowatt-hour of new energy sources based on the differences between the carbon emissions and new energy power generation of different new energy installed capacity scenarios and the baseline installed capacity scenario, so as to evaluate the equivalent carbon emission reduction benefits of new energy power generation in the power system under different installed capacity scenarios in the future.

[0006] Furthermore, the aforementioned characteristic model establishing the relationship between fossil fuel unit output and carbon emissions based on fossil fuel unit output includes: the carbon emission characteristic model is obtained using the following formula:

[0007]

[0008] Among them, E g,r NCV represents the carbon emissions generated by the g-th fossil fuel unit burning the r-th fuel during time period t. g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t, CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit, OF g,r P represents the carbon oxidation rate of fuel. g (t) represents the power generation of the g-th fossil fuel unit during time period t, β g (t) represents the average fuel consumption per unit of electricity generated by a fossil fuel unit at the corresponding power operating point.

[0009] Furthermore, the source, grid, load, and storage model establishes a time-series simulation and pre-evaluation model for carbon emissions in the power system, including: with the goal of maximizing the absorption of new energy sources, based on the source, grid, load, and storage model, establishing the objective function and constraints of the time-series simulation and pre-evaluation model for carbon emissions in the power system.

[0010] Furthermore, the objective function is as follows:

[0011]

[0012] Where N represents the total number of regional power grids, n represents any regional power grid; T represents the total length of the solution period; Pn w (t) represents the wind power output of the wind farm in region n during time period t, P n pv (t) represents the photovoltaic output of the photovoltaic power station in region n during time period t.

[0013] Furthermore, the constraints include load balance constraints, conventional unit output constraints, conventional unit ramp-up constraints, unit start-up and shutdown operation state logic constraints, conventional unit minimum start-up and shutdown time constraints, power grid line transmission capacity constraints, system reserve capacity constraints, new energy output constraints, energy storage capacity constraints, energy storage output range constraints, energy storage charge and discharge times constraints, energy storage charge and discharge state consistency constraints, and total carbon emissions of the power system constraints.

[0014] Furthermore, the method of obtaining the carbon emission reduction intensity index per kilowatt-hour of new energy based on the difference between carbon emissions and new energy power generation in different new energy installation scenarios and the benchmark installation scenario includes: obtaining the carbon emission reduction intensity index CAI_NE per kilowatt-hour of new energy using the following method: CAI_NE = ΔC 减排量 / ΔE 新能源 ; where ΔC 减排量 This represents the carbon emission reduction compared to the baseline installation scenario, and is the difference in carbon emissions between different new energy installation scenarios and the baseline installation scenario; ΔE 新能源 This represents the increase in new energy power generation compared to the baseline installed capacity scenario, and is the difference in new energy power generation between different new energy installed capacity scenarios and the baseline installed capacity scenario.

[0015] Secondly, embodiments of the present invention also provide an apparatus for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources. The apparatus includes: a first model building unit, used to establish a characteristic model of the relationship between the output of fossil energy units and carbon emissions based on the output of fossil energy units; a second model building unit, used to establish a time-series simulation pre-evaluation model of carbon emissions in the power system based on a source-grid-load-storage model; a first processing unit, used to define a baseline installed capacity scenario and calculate the carbon emissions and new energy power generation of the baseline installed capacity scenario based on the characteristic model of the relationship between the output of fossil energy units and carbon emissions and the time-series simulation pre-evaluation model of carbon emissions in the power system; a second processing unit, used to construct different new energy installed capacity scenarios and calculate the carbon emissions and new energy power generation under different new energy installed capacity scenarios based on the characteristic model of the relationship between the output of fossil energy units and carbon emissions and the time-series simulation pre-evaluation model of carbon emissions in the power system; and a third processing unit, used to obtain the carbon emission reduction intensity index per kilowatt-hour of new energy sources based on the differences between the carbon emissions and new energy power generation under different new energy installed capacity scenarios and the baseline installed capacity scenario, so as to evaluate the equivalent carbon emission reduction benefits of new energy power generation in the power system under different future installed capacity scenarios.

[0016] Furthermore, the first model-building unit is also used to: obtain the carbon emission characteristic model using the following formula:

[0017]

[0018] Among them, E g,r NCV represents the carbon emissions generated by the g-th fossil fuel unit burning the r-th fuel during time period t. g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t, CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit, OF g,r P represents the carbon oxidation rate of fuel. g (t) represents the power generation of the g-th fossil fuel unit during time period t, β g (t) represents the average fuel consumption per unit of electricity generated by a fossil fuel unit at the corresponding power operating point.

[0019] Furthermore, the second model building unit is also used to: establish the objective function and constraints of the power system carbon emission time series simulation pre-evaluation model based on the source, grid, load and storage model, with the goal of maximizing the absorption of new energy.

[0020] Furthermore, the objective function is as follows:

[0021]

[0022] Where N represents the total number of regional power grids, n represents any regional power grid, and T represents the total length of the solution period; This represents the wind power output of the wind farm within region n during time period t. This represents the photovoltaic output of a photovoltaic power station within region n during time period t.

[0023] Furthermore, the constraints include load balance constraints, conventional unit output constraints, conventional unit ramp-up constraints, unit start-up and shutdown operation state logic constraints, conventional unit minimum start-up and shutdown time constraints, power grid line transmission capacity constraints, system reserve capacity constraints, new energy output constraints, energy storage capacity constraints, energy storage output range constraints, energy storage charge and discharge times constraints, energy storage charge and discharge state consistency constraints, and total carbon emissions of the power system constraints.

[0024] Furthermore, the third processing unit is also used to: obtain the carbon emission reduction intensity index CAI_NE of new energy per kilowatt-hour as follows: CAI_NE=ΔC 减排量 / ΔE 新能源 ; where ΔC 减排量 This represents the carbon emission reduction compared to the baseline installation scenario, and is the difference in carbon emissions between different new energy installation scenarios and the baseline installation scenario; ΔE 新能源This represents the increase in new energy power generation compared to the baseline installed capacity scenario, and is the difference in new energy power generation between different new energy installed capacity scenarios and the baseline installed capacity scenario.

[0025] Thirdly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the methods provided in the above embodiments.

[0026] Fourthly, embodiments of the present invention also provide an electronic device, including: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the methods provided in the above embodiments.

[0027] The method and apparatus for determining the carbon emission reduction intensity index per kilowatt-hour of new energy provided in this invention establish a characteristic model of the relationship between fossil energy unit output and carbon emissions based on fossil energy unit output. Based on a source-grid-load-storage model, a time-series simulation pre-assessment model of power system carbon emissions is established to clarify the baseline installed capacity scenario. Based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time-series simulation pre-assessment model of power system carbon emissions, the carbon emissions and new energy power generation of the baseline installed capacity scenario are calculated. Different new energy installed capacity scenarios are constructed, and based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time-series simulation pre-assessment model of power system carbon emissions... The model calculates carbon emissions and power generation under different renewable energy installation scenarios, as well as the differences between carbon emissions and power generation under different renewable energy installation scenarios and a benchmark installation scenario, to obtain a renewable energy carbon emission reduction intensity index per kilowatt-hour. This index is used to assess the equivalent carbon emission reduction benefits of renewable energy power generation in the power system under different installation scenarios in the future. It can accurately estimate the equivalent carbon emission reduction benefits of renewable energy grid-connected power generation, provide correct guidance for the healthy and orderly development of renewable energy, provide an important basis for CER (carbon emission reduction credit) and green certificate carbon credit for renewable energy power generation projects, and also provide a scientific decision-making basis for renewable energy development timing, power system flexibility improvement, and regional differentiated planning. Attached Figure Description

[0028] Figure 1 An exemplary flowchart of a method for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources according to an embodiment of the present invention is shown;

[0029] Figure 2 This figure shows a trend chart of carbon emission reduction benefits per kilowatt-hour for new energy power generation according to an embodiment of the present invention;

[0030] Figure 3 A schematic diagram of a device for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources according to an embodiment of the present invention is shown. Detailed Implementation

[0031] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0032] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0033] It is important to understand that the equivalent carbon emission reduction benefits of new energy power generation should not only be calculated based on the carbon emission reduction brought about by the replacement of fossil energy power generation by new energy power generation, but also take into account the indirect carbon emission increment brought about by power system flexibility improvement measures (deep peak shaving of thermal power and energy storage configuration) implemented to absorb new energy.

[0034] Figure 1 An exemplary flowchart of a method for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources according to an embodiment of the present invention is shown.

[0035] like Figure 1 As shown, the method includes:

[0036] Step S101: Based on the output of fossil fuel units, establish a characteristic model of the relationship between the output of fossil fuel units and carbon emissions.

[0037] Further, step S101 includes:

[0038] The carbon emission characteristics model is obtained using the following formula:

[0039]

[0040] Among them, E g,r NCV represents the carbon emissions generated by the g-th fossil fuel unit burning the r-th fuel during time period t. g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t, CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit, OF g,r P represents the carbon oxidation rate of fuel. g (t) represents the power generation of the g-th fossil fuel unit during time period t, β g(t) represents the average fuel consumption per unit of electricity generated by a fossil fuel unit at the corresponding power operating point.

[0041] Specifically, the specific energy consumption characteristic of fossil fuel generator sets is a function of the unit's output. The specific energy consumption characteristic above the unit's rated minimum output can be expressed as a quadratic function, as shown in the following formula.

[0042]

[0043] Where: β g (t) represents the average fuel consumption per unit of electricity generated by the thermal power unit at the corresponding power operating point, i.e., the specific fuel consumption characteristic; P g,t Let A be the power output of the g-th fossil fuel unit during time period t; g B g C g The specific energy consumption characteristic coefficient of fossil energy units can be obtained by fitting, and can be determined based on the measured or designed specific energy consumption characteristic curve of the unit. The measured value should be preferred.

[0044] As the unit load decreases, the standard coal consumption rate for power generation gradually increases, especially when the unit load rate drops below the rated minimum output, the rate of increase accelerates rapidly. The carbon dioxide emissions from fossil fuel power generation by fossil fuel units are calculated time-by-time using the following formula:

[0045]

[0046] In the formula: E g,r NCV represents the carbon emissions generated by the g-th fossil fuel unit burning the r-th fuel during time period t. g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t, CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit, OF g,r The carbon oxidation rate of the fuel.

[0047] Step S102: Based on the source, grid, load, and storage model, establish a time-series simulation pre-assessment model for carbon emissions from the power system.

[0048] Steps S101 and S102 are not in any particular order; they can be interchanged or executed in parallel.

[0049] Further, step S102 includes:

[0050] With the goal of maximizing the absorption of new energy sources, an objective function and constraints are established for a time-series simulation and pre-evaluation model of carbon emissions in the power system, based on a source, grid, load, and storage model.

[0051] The above embodiments aim to maximize the absorption of new energy sources, establish a time-series simulation model of power system carbon emissions that takes into account the characteristics of deep peak shaving consumption and the interaction characteristics of power generation, grid, load and storage, and improve the accuracy of power system carbon emission prediction.

[0052] Furthermore, the objective function is as follows:

[0053]

[0054] Where N represents the total number of regional power grids, n represents any regional power grid; T represents the total length of the solution period; P n w (t) represents the wind power output of the wind farm in region n during time period t, P n pv (t) represents the photovoltaic output of the photovoltaic power station in region n during time period t.

[0055] Furthermore, the constraints include load balance constraints, conventional unit output constraints, conventional unit ramp-up constraints, unit start-up and shutdown operation status logic constraints, conventional unit minimum start-up and shutdown time constraints, power grid transmission capacity constraints, system reserve capacity constraints, renewable energy output constraints, energy storage capacity constraints, energy storage output range constraints, energy storage charge and discharge times constraints, energy storage charge and discharge status consistency constraints, and total carbon emissions of the power system constraints.

[0056] Specifically, the constraints include:

[0057] (1) Load balance constraint

[0058]

[0059] In the formula: n and m represent the grid zone number; N represents the number of grid zones; g is the thermal power unit number; N G,n This represents the total number of conventional generating units within region n. P represents the renewable energy output of region n during time period t; g,n (t) represents the output of the g-th conventional unit in region n during time period t; The load within region n; For power exchange between region n and region m; This represents the power transmitted by the tie line in region n during time period t.

[0060] (2) Output constraints of conventional units

[0061]

[0062]

[0063] In the formula: X represents the upper and lower limits of the output of the g-th conventional unit within region n; g,n (t) represents the operating status of the g-th conventional generating unit in the region during time period t. It is a binary variable, where 0 indicates that the unit is shut down and 1 indicates that the unit is running. ΔP g,n (t) represents the power of the g-th conventional unit in the region during time period t;

[0064] (3) Ramp-up constraints for conventional units

[0065] P g,n (t+1)-P g,n (t)≤ΔP g,up ;

[0066] P g,n (t)-P g,n (t+1)≤ΔP g,down ;

[0067] Where: ΔP g,up and ΔP g,down These represent the uphill and downhill ramp rates of conventional generator units, respectively.

[0068] (4) Logical constraints on unit start-up and shutdown operation status

[0069]

[0070] In the formula: Y g (t) and Z g (t) represents the start-up and shutdown states of the g-th generating unit at time t, both of which are binary variables. For Y, 0 indicates that it is not in the start-up state, and 1 indicates that it is starting up; for Z, 0 indicates that it is not in the shutdown state, and 1 indicates that it is shutting down. This constraint is a logical constraint on the start-up, shutdown, and operating states of the generating units, ensuring that each state variable is logically consistent during the unit combination process.

[0071] (5) Minimum start-up and shutdown time constraints for conventional units

[0072] Y g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1;

[0073] Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1;

[0074] In the formula: k is determined by the minimum start-up or shutdown time parameter of the unit, which reflects the minimum start-up or shutdown time step. This constraint is mainly due to the constraints of the unit's physical characteristics, energy consumption and operating costs, and the unit cannot be frequently started and stopped.

[0075] (6) Power line transmission capacity constraints

[0076]

[0077] In the formula, This indicates the line transmission capacity limit between region n and region m;

[0078] (7) System standby capacity constraints

[0079]

[0080] In the formula: R P and R N They are respectively for positive rotation standby and negative rotation standby; Let n be the reliable capacity of new energy power generation within region n;

[0081] (8) Constraints on new energy output

[0082] 0≤P n w (t)≤P n W (t);

[0083]

[0084] In the formula: P n W (t) refers to the theoretical power output of wind farm n in region during time period t. This refers to the photovoltaic power output of photovoltaic power station n in region during time period t.

[0085] (9) Energy storage capacity constraints

[0086]

[0087] In the formula: The energy storage capacity of energy storage unit i during time period t; These represent the upper and lower limits of the energy storage capacity of energy storage unit i, respectively. These represent the discharge / charge power of energy storage unit i during time period t; T represents the charge and discharge efficiency of the energy storage unit. i PH The energy storage capacity adjustment cycle of energy storage unit i. These are the initial energy storage capacity of energy storage unit i during its adjustment period;

[0088] (10) Constraints on energy storage output range

[0089]

[0090] In the formula: These are the discharge / charge state variables of energy storage unit i at time t; These represent the upper limits of the discharge / charging power of the energy storage unit;

[0091] (11) Constraints on the number of energy storage charge and discharge cycles

[0092]

[0093] In the formula: The maximum number of discharge / charge cycles per single regulation cycle for each energy storage unit i;

[0094] (12) Consistency constraint of energy storage charging and discharging state

[0095]

[0096] g PH (t)+d PH (t)”1;

[0097] In the formula, g PH (t), d PH (t) represent the discharge / charge state variables of the entire system's energy storage units at time t;

[0098] (13) Constraints on total carbon emissions from the power system

[0099]

[0100] In the formula, E n This indicates the annual carbon emission limit for provincial power grids.

[0101] Step S103: Define the baseline installed capacity scenario, and calculate the carbon emissions and renewable energy generation of the baseline installed capacity scenario based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time series simulation pre-evaluation model of power system carbon emissions.

[0102] Specifically, taking a provincial power grid as an example, we can clarify the situation of new energy power generation under the benchmark installed capacity scenario, and on this basis, conduct carbon emission sensitivity analysis under different new energy installed capacity penetration rates.

[0103] Step S104: Construct different new energy installation scenarios, and calculate the carbon emissions and new energy power generation under different new energy installation scenarios based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time series simulation pre-evaluation model of power system carbon emissions.

[0104] Steps S103 and S104 are not in any particular order; they can be interchanged or executed in parallel.

[0105] Step S105: Based on the difference between the carbon emissions and the renewable energy power generation in different renewable energy installation scenarios and the benchmark installation scenario, obtain the renewable energy carbon emission reduction intensity index per kilowatt-hour, which can be used to evaluate the equivalent carbon emission reduction benefits of renewable energy power generation in the power system under different installation scenarios in the future.

[0106] Further, step S105 includes:

[0107] The carbon emission reduction intensity index (CAI_NE) per kilowatt-hour of new energy is obtained as follows:

[0108] CAI_NE=ΔC 减排量 / ΔE 新能源 ;

[0109] Where, ΔC 减排量 This represents the carbon emission reduction compared to the baseline installation scenario, and is the difference in carbon emissions between different new energy installation scenarios and the baseline installation scenario; ΔE 新能源 This represents the increase in new energy power generation compared to the baseline installed capacity scenario, and is the difference in new energy power generation between different new energy installed capacity scenarios and the baseline installed capacity scenario.

[0110] Specifically, ΔC 减排量 ΔE can be obtained by subtracting the carbon emissions of the baseline installed capacity scenario from the actual carbon emissions. 新能源 It can be obtained by subtracting the renewable energy generation of the benchmark installed capacity scenario from the actual renewable energy generation.

[0111] Considering the interplay between various factors, including the energy consumption characteristics of renewable energy generation, energy storage conversion, and the coal consumption characteristics of fossil fuel units, this paper proposes the Carbon Abatement Intensity per Unit Generation of Renewable Energy Generation (CAI_NE) index. This index quantitatively characterizes the carbon emission reduction capacity (gCO2 / kWh) of a unit of renewable energy generation (kWh) on the power system. The physical meaning of CAI_NE lies in the reduction of system carbon emissions corresponding to every 1 kWh of additional renewable energy generation. By directly quantifying the contribution of a unit of renewable energy generation to system carbon emission reduction, it reveals the dynamic evolution of the "renewable energy-carbon" coupling relationship, which can be used to analyze the equivalent carbon emission reduction benefits of renewable energy generation and its saturation point. By effectively replacing fossil fuel power generation with carbon emission reductions, and then deducting the carbon emission increments resulting from flexibility adjustment measures implemented to increase renewable energy generation (such as deep peak shaving of thermal power and the configuration of energy storage), this approach breaks through the calculation model based on the grid carbon dioxide baseline emission factor (CM) under the CDM mechanism.

[0112] The above embodiments establish a characteristic model of the relationship between fossil fuel unit output and carbon emissions based on fossil fuel unit output. Based on a source-grid-load-storage model, a time-series simulation and pre-assessment model of power system carbon emissions is established to define a baseline installed capacity scenario. Based on the characteristic model of the relationship between fossil fuel unit output and carbon emissions and the time-series simulation and pre-assessment model of power system carbon emissions, the carbon emissions and renewable energy generation of the baseline installed capacity scenario are calculated. Different renewable energy installed capacity scenarios are constructed, and based on the characteristic model of the relationship between fossil fuel unit output and carbon emissions and the time-series simulation and pre-assessment model of power system carbon emissions, different renewable energy installed capacities are calculated. The carbon emissions and renewable energy generation under different scenarios, as well as the differences between the carbon emissions and renewable energy generation under different renewable energy installation scenarios and the benchmark installation scenario, yield the renewable energy per-kilowatt-hour carbon emission reduction intensity index. This index is used to assess the equivalent carbon emission reduction benefits of renewable energy generation in the power system under different installation scenarios in the future. It can accurately estimate the equivalent carbon emission reduction benefits of renewable energy grid-connected power generation, provide correct guidance for the healthy and orderly development of renewable energy, provide an important basis for the CER (carbon emission reduction credit) and green certificate carbon credit of renewable energy power generation projects, and also provide a scientific decision-making basis for the timing of renewable energy development, the improvement of power system flexibility, and regional differentiated planning.

[0113] Example 1

[0114] Specifically, taking a provincial power grid as an example, keeping the load and other boundaries unchanged, and considering the deep peak shaving of thermal power, the adjustment range is 20% to 100% of the installed capacity. Using the method for determining the carbon emission reduction intensity index of new energy per kilowatt-hour provided in the above embodiment, the carbon emission reduction intensity index of new energy per kilowatt-hour under different scenarios is obtained. Based on the carbon emission reduction intensity index of new energy per kilowatt-hour, the changes in carbon emissions of the power system under different new energy installed capacities are analyzed. Figure 2 A graph showing the changing trend of carbon emission reduction benefits per kilowatt-hour for new energy power generation according to an embodiment of the present invention is provided. Figure 2 As shown, the changes in carbon emissions of the power system under different renewable energy installed capacities are as follows:

[0115] (1) The amount of electricity consumed by new energy sources and the carbon emissions of the power system gradually reach saturation as the installed capacity of new energy sources increases;

[0116] (2) The carbon emission reduction benefit per kilowatt-hour of new energy power generation shows a decreasing trend and gradually saturates as the installed capacity of new energy increases.

[0117] Figure 3 A schematic diagram of a device for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources according to an embodiment of the present invention is shown.

[0118] like Figure 3 As shown, the device includes:

[0119] The first model building unit 301 is used to establish a characteristic model of the relationship between the output of fossil energy units and carbon emissions based on the output of fossil energy units.

[0120] The second model building unit 302 is used to build a time-series simulation and pre-assessment model of carbon emissions from the power system based on the source, grid, load and storage model.

[0121] The first processing unit 303 is used to define the baseline installed capacity scenario and, based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time series simulation pre-evaluation model of power system carbon emissions, calculate the carbon emissions and new energy power generation of the baseline installed capacity scenario.

[0122] The second processing unit 304 is used to construct different new energy installation scenarios, and calculate the carbon emissions and new energy power generation under different new energy installation scenarios based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time series simulation pre-evaluation model of power system carbon emissions.

[0123] The third processing unit 305 is used to obtain the carbon emission reduction intensity index per kilowatt-hour of new energy based on the difference between the carbon emissions and the new energy power generation in different new energy installation scenarios and the benchmark installation scenario, so as to evaluate the equivalent carbon emission reduction benefits of new energy power generation in the power system under different installation scenarios in the future.

[0124] Furthermore, the first model building unit 301 is also used for:

[0125] The carbon emission characteristics model is obtained using the following formula:

[0126]

[0127] Among them, E g,r NCV represents the carbon emissions generated by the g-th fossil fuel unit burning the r-th fuel during time period t. g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t, CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit, OF g,r P represents the carbon oxidation rate of fuel. g (t) represents the power generation of the g-th fossil fuel unit during time period t, β g (t) represents the average fuel consumption per unit of electricity generated by a fossil fuel unit at the corresponding power operating point.

[0128] Furthermore, the second model building unit 302 is used for:

[0129] With the goal of maximizing the absorption of new energy sources, an objective function and constraints are established for a time-series simulation and pre-evaluation model of carbon emissions in the power system, based on a source, grid, load, and storage model.

[0130] Furthermore, the objective function is as follows:

[0131]

[0132] Where N represents the total number of regional power grids, n represents any regional power grid; T represents the total length of the solution period; P n w (t) represents the wind power output of the wind farm in region n during time period t, P n pv (t) represents the photovoltaic output of the photovoltaic power station in region n during time period t.

[0133] Furthermore, the constraints include load balance constraints, conventional unit output constraints, conventional unit ramp-up constraints, unit start-up and shutdown operation status logic constraints, conventional unit minimum start-up and shutdown time constraints, power grid transmission capacity constraints, system reserve capacity constraints, renewable energy output constraints, energy storage capacity constraints, energy storage output range constraints, energy storage charge and discharge times constraints, energy storage charge and discharge status consistency constraints, and total carbon emissions of the power system constraints.

[0134] Furthermore, the third processing unit 305 is also used for:

[0135] The carbon emission reduction intensity index (CAI_NE) per kilowatt-hour of new energy is obtained as follows:

[0136] CAI_NE=ΔC 减排量 / ΔE 新能源 ;

[0137] Where, ΔC 减排量 This represents the carbon emission reduction compared to the baseline installation scenario, and is the difference in carbon emissions between different new energy installation scenarios and the baseline installation scenario; ΔE 新能源 This represents the increase in new energy power generation compared to the baseline installed capacity scenario, and is the difference in new energy power generation between different new energy installed capacity scenarios and the baseline installed capacity scenario.

[0138] The above embodiments establish a characteristic model of the relationship between fossil fuel unit output and carbon emissions based on fossil fuel unit output. Based on a source-grid-load-storage model, a time-series simulation and pre-assessment model of power system carbon emissions is established to define a baseline installed capacity scenario. Based on the characteristic model of the relationship between fossil fuel unit output and carbon emissions and the time-series simulation and pre-assessment model of power system carbon emissions, the carbon emissions and renewable energy generation of the baseline installed capacity scenario are calculated. Different renewable energy installed capacity scenarios are constructed, and based on the characteristic model of the relationship between fossil fuel unit output and carbon emissions and the time-series simulation and pre-assessment model of power system carbon emissions, the carbon emissions and renewable energy generation of different renewable energy scenarios are calculated. The carbon emissions and renewable energy generation under different installed capacity scenarios, as well as the differences between the carbon emissions and renewable energy generation under different installed capacity scenarios and the benchmark installed capacity scenario, yield the renewable energy per kilowatt-hour carbon emission reduction intensity index. This index is used to assess the equivalent carbon emission reduction benefits of renewable energy generation in the power system under different installed capacity scenarios in the future. It can accurately estimate the equivalent carbon emission reduction benefits of renewable energy grid-connected power generation, provide correct guidance for the healthy and orderly development of renewable energy, provide an important basis for the CER (carbon emission reduction credit) and green certificate carbon credit of renewable energy power generation projects, and also provide a scientific decision-making basis for the timing of renewable energy development, the improvement of power system flexibility, and regional differentiated planning.

[0139] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0140] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for determining the carbon emission reduction intensity index per kilowatt-hour of new energy provided in the above embodiments.

[0141] This invention also provides an electronic device, including: a processor; a memory for storing processor-executable instructions; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method for determining the carbon emission reduction intensity index of new energy per kilowatt-hour provided in the above embodiments.

[0142] The invention has been described with reference to a few embodiments. However, as will be known to those skilled in the art, and as defined in the appended claims, other embodiments besides those disclosed above fall equivalently within the scope of the invention.

[0143] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the art, unless otherwise expressly defined herein. All references to “a / the / the [device, component, etc.]” ​​are openly interpreted as at least one instance of said device, component, etc., unless otherwise expressly stated. The steps of any method disclosed herein need not be performed in the exact order disclosed unless explicitly stated otherwise.

[0144] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0145] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0146] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0147] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0148] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources, characterized in that, The method includes: Based on the output of fossil fuel units, a characteristic model of the relationship between the output of fossil fuel units and carbon emissions is established. Based on the source, grid, load, and storage model, a time-series simulation and pre-assessment model for carbon emissions from the power system is established. The baseline installed capacity scenario was defined, and based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time series simulation pre-evaluation model of power system carbon emissions, the carbon emissions and renewable energy power generation of the baseline installed capacity scenario were calculated. We construct different new energy installation scenarios, and calculate the carbon emissions and new energy power generation under different new energy installation scenarios based on the characteristic model of the relationship between the output and carbon emissions of fossil energy units and the time series simulation and pre-evaluation model of carbon emissions in the power system. Based on the differences in carbon emissions and renewable energy generation between different renewable energy installation scenarios and the benchmark installation scenario, a renewable energy carbon emission reduction intensity index per kilowatt-hour is obtained to evaluate the equivalent carbon emission reduction benefits of renewable energy generation in the power system under different installation scenarios in the future.

2. The method according to claim 1, characterized in that, The aforementioned characteristic model establishing the relationship between fossil fuel power output and carbon emissions based on fossil fuel unit output includes: The carbon emission characteristics model is obtained using the following formula: Among them, E g,r NCV represents the carbon emissions generated by the g-th fossil fuel unit burning the r-th fuel during time period t. g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t, CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit, OF g,r P represents the carbon oxidation rate of fuel. g (t) represents the power generation of the g-th fossil fuel unit during time period t, β g (t) represents the average fuel consumption per unit of electricity generated by a fossil fuel unit at the corresponding power operating point.

3. The method according to claim 1, characterized in that, The aforementioned power system carbon emission time-series simulation and pre-assessment model, based on the source, grid, load, and storage model, includes: With the goal of maximizing the absorption of new energy sources, an objective function and constraints are established for a time-series simulation and pre-evaluation model of carbon emissions in the power system, based on a source, grid, load, and storage model.

4. The method according to claim 3, characterized in that, The objective function is as follows: Where N represents the total number of regional power grids, n represents any regional power grid, and T represents the total length of the solution period; This represents the wind power output of the wind farm within region n during time period t. This represents the photovoltaic output of a photovoltaic power station within region n during time period t.

5. The method according to claim 3, characterized in that, The constraints include load balance constraints, conventional unit output constraints, conventional unit ramp-up constraints, unit start-up and shutdown operation status logic constraints, conventional unit minimum start-up and shutdown time constraints, power grid transmission capacity constraints, system reserve capacity constraints, renewable energy output constraints, energy storage capacity constraints, energy storage output range constraints, energy storage charge and discharge times constraints, energy storage charge and discharge status consistency constraints, and total carbon emissions of the power system constraints.

6. The method according to claim 1, characterized in that, The carbon emission reduction intensity index per kilowatt-hour of new energy is obtained by comparing the carbon emissions and new energy power generation of different new energy installation scenarios with a benchmark installation scenario, including: The carbon emission reduction intensity index (CAI_NE) per kilowatt-hour of new energy is obtained as follows: CAI_NE=ΔC 减排量 / ΔE 新能源 ; Where, ΔC 减排量 This represents the carbon emission reduction compared to the baseline installation scenario, and is the difference in carbon emissions between different new energy installation scenarios and the baseline installation scenario; ΔE 新能源 This represents the increase in new energy power generation compared to the baseline installed capacity scenario, and is the difference in new energy power generation between different new energy installed capacity scenarios and the baseline installed capacity scenario.

7. A device for determining the carbon emission reduction intensity index per kilowatt-hour of new energy sources, characterized in that, The device includes: The first model building unit is used to establish a characteristic model of the relationship between the output of fossil energy units and carbon emissions based on the output of fossil energy units. The second model building unit is used to build a time-series simulation and pre-assessment model of carbon emissions from the power system based on the source, grid, load, and storage models. The first processing unit is used to define the baseline installed capacity scenario and, based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time series simulation pre-evaluation model of power system carbon emissions, calculate the carbon emissions and new energy power generation of the baseline installed capacity scenario. The second processing unit is used to construct different new energy installation scenarios, and calculate the carbon emissions and new energy power generation under different new energy installation scenarios based on the characteristic model of the relationship between fossil energy unit output and carbon emissions and the time series simulation pre-evaluation model of power system carbon emissions. The third processing unit is used to obtain the carbon emission reduction intensity index per kilowatt-hour of new energy based on the difference between the carbon emissions and the new energy power generation in different new energy installation scenarios and the benchmark installation scenario, so as to evaluate the equivalent carbon emission reduction benefits of new energy power generation in the power system under different installation scenarios in the future.

8. The apparatus according to claim 7, characterized in that, The first model building unit is further configured to: The carbon emission characteristics model is obtained using the following formula: Among them, E g,r NCV represents the carbon emissions generated by the g-th fossil fuel unit burning the r-th fuel during time period t. g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t, CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit, OF g,r P represents the carbon oxidation rate of fuel. g (t) represents the power generation of the g-th fossil fuel unit during time period t, β g (t) represents the average fuel consumption per unit of electricity generated by a fossil fuel unit at the corresponding power operating point.

9. The apparatus according to claim 7, characterized in that, The second model building unit is also used for: With the goal of maximizing the absorption of new energy sources, an objective function and constraints are established for a time-series simulation and pre-evaluation model of carbon emissions in the power system, based on a source, grid, load, and storage model.

10. The apparatus according to claim 9, characterized in that, The objective function is as follows: Where N represents the total number of regional power grids, n represents any regional power grid, and T represents the total length of the solution period; This represents the wind power output of the wind farm within region n during time period t. This represents the photovoltaic output of a photovoltaic power station within region n during time period t.

11. The apparatus according to claim 9, characterized in that, The constraints include load balance constraints, conventional unit output constraints, conventional unit ramp-up constraints, unit start-up and shutdown operation status logic constraints, conventional unit minimum start-up and shutdown time constraints, power grid transmission capacity constraints, system reserve capacity constraints, renewable energy output constraints, energy storage capacity constraints, energy storage output range constraints, energy storage charge and discharge times constraints, energy storage charge and discharge status consistency constraints, and total carbon emissions of the power system constraints.

12. The apparatus according to claim 7, characterized in that, The third processing unit is further configured to: The carbon emission reduction intensity index (CAI_NE) per kilowatt-hour of new energy is obtained as follows: CAI_NE=ΔC 减排量 / ΔE 新能源 ; Where, ΔC 减排量 This represents the carbon emission reduction compared to the baseline installation scenario, and is the difference in carbon emissions between different new energy installation scenarios and the baseline installation scenario; ΔE 新能源 This represents the increase in new energy power generation compared to the baseline installed capacity scenario, and is the difference in new energy power generation between different new energy installed capacity scenarios and the baseline installed capacity scenario.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-6.

14. An electronic device, comprising: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of claims 1-6.

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